Multilayer artificial neural networks are widely involved in pattern recognition, image processing, function approximation, optimality computation, etc. In order to adapt to the increasingly high task requirements, the size and the complexity of the neural network are increasing. For example, a large convolution neural network may include hundreds of layers of operations. Particularly in convolution neural networks, large amount of convolution operations may reduce the processing speed of the neural network, which may further impair the practical applications of neural networks.